Monitoring of crops in agriculture is necessary to determine optimal growing conditions to improve and maximize yields. Maximization of crop yields is critical to the agricultural industry due to the relatively low profit margins involved. Crop conditions in a particular field or area are analyzed for factors such as plant growth, irrigation, pesticides etc. The results of the analyses may be used to identify planting problems, estimate yields, adjust irrigation schedules and plan fertilizer application. The status of the crops is monitored throughout the growing cycle in order to insure that maximum crop yields may be achieved.
Optimum crop development requires maintenance of high levels of both chlorophyll and nitrogen in plants. As it is known that plant growth correlates with chlorophyll concentration, finding of low chlorophyll concentration levels is indicative of slower growth and ultimately a yield loss. Since there is a direct relationship between the nitrogen and chlorophyll levels in plants, a finding of low chlorophyll may signal the existence of low levels of nitrogen. Thus, in order to improve crop growth, farmers add nitrogen fertilizers to the soil to increase chlorophyll concentration and stimulate crop growth. Fertilizer treatments, if applied early in the crop growth cycle, can insure that slower growing crops achieve normal levels of growth.
Monitoring nitrogen levels in crops, vis-a-vis chlorophyll levels, allows a farmer to adjust application of fertilizer to compensate for shortages of nitrogen and increase crop growth.
Accurate recommendations for fertilizer nitrogen are desired to avoid inadequate or excessive application of nitrogen fertilizers. Excessive amounts of fertilizer may reduce yields and quality of certain crops. Additionally, over application of fertilizer results in added costs to a farmer, as well as increasing the potential for nitrate contamination of the environment. Thus, it is critical to obtain both accurate and timely information on nitrogen levels.
One known method of determining the nitrogen content in plants and soil involves taking samples of plants and soil and performing chemical testing. However this method requires considerable time and repeated sampling during the growing season. Additionally, a time delay exists from the time the samples are taken to the time when the nitrogen levels are ascertained and when fertilizer may be applied due to the time required for laboratory analysis. Such delay may result in the delayed application of corrective amounts of fertilizer, which may then be too late to prevent stunted crop growth.
In an effort to eliminate the delay between the times of nitrogen measurement and the application of corrective fertilizer, it has been previously suggested to utilize aerial or satellite photographs to obtain timely data on field conditions. This method involves taking a photograph from a camera mounted on an airplane or a satellite. Such photos are compared with those of areas which do not have nitrogen stress. Such a method provides improvement in analysis time but is still not real time. Additionally it requires human intervention and judgment. Information about crop status is limited to the resolution of the images. When such aerial images are digitized, a single pixel may represent an area such as a square meter. Insufficient resolution prevents accurate crop assessment. Other information which might be gleaned from higher resolution images cannot be measured.
Another approach uses a photodiode mounted on ground based platforms to monitor light reflected from a sensed area. The image is analyzed to determine the quantity of light reflected at specific wavelengths within the light spectrum of the field of view. Nitrogen levels in the crops have been related to the amount of light reflected in specific parts of the light spectrum, most notably the green and near infrared wavelength bands. Thus, the reflectance of a crop may be used to estimate the nitrogen for the plants in that crop area.
In contradistinction, however, the photodiode sensing methods suffer from inaccuracies in the early part of the crop growth cycle because the overall reflectance values are partially derived from significant areas of non-vegetation backgrounds, such as soil, which skew the reflectance value and hence the nitrogen measurements. Additionally, since one value is used, this method cannot account for deviations in reflectance readings due to shadows, tassels and row orientation of the crops.
Increasing spatial and spectral resolution can produce a more accurate image, which provides improved reflectance analysis as well as being able to differentiate individual rows or plants. However, current high resolution remote sensing approaches have met with little success because of the tremendous volumes of data generated when used over large areas at the necessary high resolutions. These methods are difficult to implement because of the large amount of data which must be stored or transferred for each image.
Thus a need exists for an image sensor which is capable of producing crop images which may be analyzed in real time for substances such as nitrogen. Furthermore, there is a need for an image sensor which accurately analyzes nitrogen content in crops independent of the stage of crop growth. Also, there is a need for a sensor which can isolate vegetation regions from an image comprising vegetation and non-vegetation areas for analysis. There is also a need for an image sensor which can determine amounts of nitrogen in discrete areas of an imaged crop area such as for a particular row. Also, there is a need for a sensor which can produce and store images of crop areas for later analysis. There is a need for an image sensor which can correct for the effects of variable ambient light on reflectance. Finally, a system is desired which may be calibrated to provide accurate prediction of additional nitrogen fertilizer required for optimum yields.